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Dr. Arthur Zimek

University of Southern Denmark
Campusvej 55
5230 Odense M
Denmark

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Email: zimek-bleibt: äöüß-@imada.sdu.dk


further information


Publications:

2016
90P. A. Jaskowiak, D. Moulavi, A. C. S. Furtado, R. J. G. B. Campello, A. Zimek, J. Sander
On strategies for building effective ensembles of relative clustering validity criteria
Knowledge and Information Systems (KAIS), 47(2): 329–354, 2016.
89G. O. Campos, A. Zimek, J. Sander, R. J. G. B. Campello, B. Micenková, E. Schubert, I. Assent, M. E. Houle
On the Evaluation of Unsupervised Outlier Detection: Measures, Datasets, and an Empirical Study
Data Mining and Knowledge Discovery, 30: 891–927, 2016.
88H.-P. Kriegel, E. Schubert, A. Zimek
The (black) art of runtime evaluation: Are we comparing algorithms or implementations?
Knowledge and Information Systems (KAIS): 1–38, 2016.
87I. Assent, C. Domeniconi, F. Gullo, A. Tagarelli, A. Zimek
MultiClust 2013: Multiple Clusterings, Multi-view Data, and Multi-source Knowledge-driven Clustering Workshop Report
ACM SIGKDD Explorations, 18(1): 35–38, 2016.
86L. Swersky, H. O. Marques, J. Sander, R. J. G. B. Campello, A. Zimek
On the Evaluation of Outlier Detection and One-Class Classification Methods
In Proceedings of the IEEE International Conference on Data Science and Advanced Analytics (DSAA), Montreal, QC, Canada: 1–10, 2016.
85G. O. Campos, A. Zimek, J. Sander, R. J. G. B. Campello, B. Micenková, E. Schubert, I. Assent, M. E. Houle
On the Evaluation of Outlier Detection: Measures, Datasets, and an Empirical Study Continued
In Proceedings of the LWDA 2016 Workshops: KDML, FGWM, FGIR, and FGDB, Potsdam, Germany: 234, 2016.
2015
84E. Schubert, A. Koos, T. Emrich, A. Züfle, K. A. Schmid, A. Zimek
A Framework for Clustering Uncertain Data
Proceedings of the VLDB Endowment, 8(12): 1976–1979, 2015.
83R. J. G. B. Campello, D. Moulavi, A. Zimek, J. Sander
Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection
ACM Transactions on Knowledge Discovery from Data (TKDD), 10(1): 5:1–51, 2015.
82A. Zimek, J. Vreeken
The Blind Men and the Elephant: On Meeting the Problem of Multiple Truths in Data from Clustering and Pattern Mining Perspectives
Machine Learning, 98(1–2): 121–155, 2015.
81E. Schubert, M. Weiler, A. Zimek
Outlier Detection and Trend Detection: Two Sides of the Same Coin
In 1st International Workshop on Event Analytics using Social Media Data at the 15th IEEE International Conference on Data Mining (ICDM), Atlantic City, NJ, 2015.
80E. Schubert, A. Zimek, H.-P. Kriegel
Fast and Scalable Outlier Detection with Approximate Nearest Neighbor Ensembles
In Proceedings of the 20th International Conference on Database Systems for Advanced Applications (DASFAA), Hanoi, Vietnam: 19–36, 2015.
79H. O. Marques, R. J. G. B. Campello, A. Zimek, J. Sander
On the Internal Evaluation of Unsupervised Outlier Detection
In Proceedings of the 27th International Conference on Scientific and Statistical Database Management (SSDBM), San Diego, CA: 7:1–12, 2015.
78J. von Brünken, M. E. Houle, A. Zimek
Intrinsic Dimensional Outlier Detection in High-Dimensional Data
Technical Report, No. NII-2015-003E, National Institute of Informatics, 2015.
2014
77E. Schubert, A. Zimek, H.-P. Kriegel
Local Outlier Detection Reconsidered: a Generalized View on Locality with Applications to Spatial, Video, and Network Outlier Detection
Data Mining and Knowledge Discovery, 28(1): 190–237, 2014.
76A. Zimek, I. Assent, J. Vreeken
Frequent Pattern Mining Algorithms for Data Clustering
In C. C. Aggarwal, J. Han (ed.): Frequent Pattern Mining, Springer: 403–423, 2014.
75D. Moulavi, P. A. Jaskowiak, R. J. G. B. Campello, A. Zimek, J. Sander
Density-based Clustering Validation
In Proceedings of the 14th SIAM International Conference on Data Mining (SDM), Philadelphia, PA: 839–847, 2014.
74E. Schubert, A. Zimek, H.-P. Kriegel
Generalized Outlier Detection with Flexible Kernel Density Estimates
In Proceedings of the 14th SIAM International Conference on Data Mining (SDM), Philadelphia, PA: 542–550, 2014.
73M. Pourrajabi, D. Moulavi, R. J. G. B. Campello, A. Zimek, J. Sander, R. Goebel
Model Selection for Semi-Supervised Clustering
In Proceedings of the 17th International Conference on Extending Database Technology (EDBT), Athens, Greece: 331–342, 2014.
72A. Züfle, T. Emrich, K. A. Schmid, N. Mamoulis, A. Zimek, M. Renz
Representative Clustering of Uncertain Data
In Proceedings of the 20th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), New York, NY: 243–252, 2014.
71A. Zimek, R. J. G. B. Campello, J. Sander
Data Perturbation for Outlier Detection Ensembles
In Proceedings of the 26th International Conference on Scientific and Statistical Database Management (SSDBM), Aalborg, Denmark: 13:1–12, 2014.
70J. Li, J. Sander, R. J. G. B. Campello, A. Zimek
Active Learning Strategies for Semi-Supervised DBSCAN
In Proceedings of the 27th Canadian Conference on Artificial Intelligence (Canadian AI), Montréal, QC, Canada: 179–190, 2014.
69X. H. Dang, I. Assent, R. T. Ng, A. Zimek, E. Schubert
Discriminative Features for Identifying and Interpreting Outliers
In Proceedings of the 30th International Conference on Data Engineering (ICDE), Chicago, IL: 88–99, 2014.
2013
68R. J. G. B. Campello, D. Moulavi, A. Zimek, J. Sander
A framework for semi-supervised and unsupervised optimal extraction of clusters from hierarchies
Data Mining and Knowledge Discovery, 27(3): 344–371, 2013.
67K. Sim, V. Gopalkrishnan, A. Zimek, G. Cong
A survey on enhanced subspace clustering
Data Mining and Knowledge Discovery, 26(2): 332–397, 2013.
66A. Zimek, R. J. G. B. Campello, J. Sander
Ensembles for Unsupervised Outlier Detection: Challenges and Research Questions
ACM SIGKDD Explorations, 15(1): 11–22, 2013.
65A. Zimek
Clustering High-Dimensional Data
In C. C. Aggarwal, C. K. Reddy (ed.): Data Clustering: Algorithms and Applications, CRC Press: 201–230, 2013.
64E. Schubert, A. Zimek, H.-P. Kriegel
Geodetic Distance Queries on R-Trees for Indexing Geographic Data
In Proceedings of the 13th International Symposium on Spatial and Temporal Databases (SSTD), Munich, Germany: 146–164, 2013.
63A. Zimek, M. Gaudet, R. J. G. B. Campello, J. Sander
Subsampling for Efficient and Effective Unsupervised Outlier Detection Ensembles
In Proceedings of the 19th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), Chicago, IL: 428–436, 2013.
62E. Achtert, H.-P. Kriegel, E. Schubert, A. Zimek
Interactive Data Mining with 3D-Parallel-Coordinate-Trees
In Proceedings of the ACM International Conference on Management of Data (SIGMOD), New York City, NY: 1009–1012, 2013.
61A. Zimek, E. Schubert, H.-P. Kriegel
Outlier Detection in High-Dimensional Data
Tutorial at the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Gold Coast, Australia, 2013.
2012
60A. Zimek, E. Schubert, H.-P. Kriegel
A Survey on Unsupervised Outlier Detection in High-Dimensional Numerical Data
Statistical Analysis and Data Mining, 5(5): 363–387, 2012.
59H.-P. Kriegel, P. Kröger, A. Zimek
Subspace Clustering
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2(4): 351–364, 2012.
58H.-P. Kriegel, P. Kröger, E. Schubert, A. Zimek
Outlier Detection in Arbitrarily Oriented Subspaces
In Proceedings of the 12th IEEE International Conference on Data Mining (ICDM), Brussels, Belgium: 379–388, 2012.
57E. Ntoutsi, A. Zimek, T. Palpanas, P. Kröger, H.-P. Kriegel
Density-based Projected Clustering over High Dimensional Data Streams
In Proceedings of the 12th SIAM International Conference on Data Mining (SDM), Anaheim, CA: 987–998, 2012.
56E. Schubert, R. Wojdanowski, A. Zimek, H.-P. Kriegel
On Evaluation of Outlier Rankings and Outlier Scores
In Proceedings of the 12th SIAM International Conference on Data Mining (SDM), Anaheim, CA: 1047–1058, 2012.
55E. Achtert, S. Goldhofer, H.-P. Kriegel, E. Schubert, A. Zimek
Evaluation of Clusterings – Metrics and Visual Support
In Proceedings of the 28th International Conference on Data Engineering (ICDE), Washington, DC: 1285–1288, 2012.
54A. Zimek, E. Schubert, H.-P. Kriegel
Outlier Detection in High-Dimensional Data
Tutorial at the 12th International Conference on Data Mining (ICDM), Brussels, Belgium, 2012.
2011
53H.-P. Kriegel, P. Kröger, J. Sander, A. Zimek
Density-based clustering
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 1(3): 231–240, 2011.
52H.-P. Kriegel, E. Schubert, A. Zimek
Evaluation of Multiple Clustering Solutions
In 2nd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings Held in Conjunction with ECML PKDD 2011, Athens, Greece: 55–66, 2011.
51J. Vreeken, A. Zimek
When Pattern Met Subspace Cluster – A Relationship Story
In 2nd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings Held in Conjunction with ECML PKDD 2011, Athens, Greece: 7–18, 2011.
50H.-P. Kriegel, P. Kröger, E. Schubert, A. Zimek
Interpreting and Unifying Outlier Scores
In Proceedings of the 11th SIAM International Conference on Data Mining (SDM), Mesa, AZ: 13–24, 2011.
49T. Bernecker, M. E. Houle, H.-P. Kriegel, P. Kröger, M. Renz, E. Schubert, A. Zimek
Quality of Similarity Rankings in Time Series
In Proceedings of the 12th International Symposium on Spatial and Temporal Databases (SSTD), Minneapolis, MN: 422–440, 2011.
48E. Achtert, A. Hettab, H.-P. Kriegel, E. Schubert, A. Zimek
Spatial Outlier Detection: Data, Algorithms, Visualizations
In Proceedings of the 12th International Symposium on Spatial and Temporal Databases (SSTD), Minneapolis, MN: 512–516, 2011.
47H.-P. Kriegel, P. Kröger, E. Ntoutsi, A. Zimek
Density Based Subspace Clustering over Dynamic Data
In Proceedings of the 23rd International Conference on Scientific and Statistical Database Management (SSDBM), Portland, OR: 387–404, 2011.
46T. Bernecker, F. Graf, H.-P. Kriegel, C. Moennig, A. Zimek
BeyOND – Unleashing BOND
In Proceedings of the 37th International Conference on Very Large Data Bases (VLDB) Workshop on Ranking in Databases (DBRank), Seattle, WA: 34–39, 2011.
45H.-P. Kriegel, E. Ntoutsi, M. Spiliopoulou, G. Tsoumakas, A. Zimek
Mining Complex Dynamic Data
Tutorial at the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD), Athens, Greece, 2011.
2010
44A. Zimek, F. Buchwald, E. Frank, S. Kramer
A Study of Hierarchical and Flat Classification of Proteins
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 7(3): 563–571, 2010.
43J. Aßfalg, J. Gong, H.-P. Kriegel, A. Pryakhin, T. Wei, A. Zimek
Investigating a Correlation between Subcellular Localization and Fold of Proteins
Journal of Universal Computer Science, 16(5): 604–621, 2010.
42E. Achtert, H.-P. Kriegel, L. Reichert, E. Schubert, R. Wojdanowski, A. Zimek
Visual Evaluation of Outlier Detection Models
In Proceedings of the 15th International Conference on Database Systems for Advanced Applications (DASFAA), Tsukuba, Japan: 396–399, 2010.
41K. Kawagoe, T. Bernecker, H.-P. Kriegel, M. Renz, A. Zimek, and A. Züfle
Similarity Search in Time Series of Dynamical Model-based Systems
In Proceedings of the 21st International Conference on Database and Expert Systems Applications (DEXA), 2nd Workshop on Database Technology for Life Sciences and Medicine (DBLM), Bilbao, Spain: 110–114, 2010.
40M. E. Houle, H.-P. Kriegel, P. Kröger, E. Schubert, A. Zimek
Can Shared-Neighbor Distances Defeat the Curse of Dimensionality?
In Proceedings of the 22nd International Conference on Scientific and Statistical Database Management (SSDBM), Heidelberg, Germany: 482–500, 2010.
39T. Bernecker, T. Emrich, F. Graf, H.-P. Kriegel, P. Kröger, M. Renz, E. Schubert, A. Zimek
Subspace Similarity Search: Efficient k-NN Queries in Arbitrary Subspaces
In Proceedings of the 22nd International Conference on Scientific and Statistical Database Management (SSDBM), Heidelberg, Germany: 555–564, 2010.
38T. Bernecker, T. Emrich, F. Graf, H.-P. Kriegel, P. Kröger, M. Renz, E. Schubert, A. Zimek
Subspace Similarity Search Using the Ideas of Ranking and Top-k Retrieval
In Proceedings of the 26th International Conference on Data Engineering (ICDE) Workshop on Ranking in Databases (DBRank), Long Beach, CA: 4–9, 2010.
37I. Färber, S. Günnemann, H.-P. Kriegel, P. Kröger, E. Müller, E. Schubert, T. Seidl, A. Zimek
On Using Class-Labels in Evaluation of Clusterings
In MultiClust: 1st International Workshop on Discovering, Summarizing and Using Multiple Clusterings Held in Conjunction with KDD 2010, Washington, DC, 2010.
36H.-P. Kriegel, A. Zimek
Subspace Clustering, Ensemble Clustering, Alternative Clustering, Multiview Clustering: What Can We Learn From Each Other?
In MultiClust: 1st International Workshop on Discovering, Summarizing and Using Multiple Clusterings Held in Conjunction with KDD 2010, Washington, DC, 2010.
35H.-P. Kriegel, P. Kröger, E. Ntoutsi, A. Zimek
Towards subspace clustering on dynamic data: an incremental version of PreDeCon
In StreamKDD'10 - 1st International Workshop on Novel Data Stream Pattern Mining Techniques Held in Conjunction with KDD 2010, Washington, DC: 31–38, 2010.
34H.-P. Kriegel, P. Kröger, A. Zimek
Outlier Detection Techniques
Tutorial at the 16th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), Washington, DC, 2010.
33H.-P. Kriegel, P. Kröger, A. Zimek
Outlier Detection Techniques
Tutorial at the 10th SIAM International Conference on Data Mining (SDM), Columbus, OH, 2010.
2009
32H.-P. Kriegel, P. Kröger, A. Zimek
Clustering High Dimensional Data: A Survey on Subspace Clustering, Pattern-based Clustering, and Correlation Clustering
ACM Transactions on Knowledge Discovery from Data (TKDD), 3(1): 1–58, 2009.
31A. Zimek
Correlation Clustering
ACM SIGKDD Explorations, 11(1): 53–54, 2009.
30G. Moise, A. Zimek, P. Kröger, H.-P. Kriegel, J. Sander
Subspace and Projected Clustering: Experimental Evaluation and Analysis
Knowledge and Information Systems (KAIS), 21(3): 299–326, 2009.
29J. Aßfalg, J. Gong, H.-P. Kriegel, A. Pryakhin, T. Wei, A. Zimek
Supervised Ensembles of Prediction Methods for Subcellular Localization
Journal of Bioinformatics and Computational Biology, 7(2): 269–285, 2009.
28P. Kröger, A. Zimek
Subspace Clustering Techniques
In L. Liu, M. T. Özsu (ed.): Encyclopedia of Database Systems, Springer: 2873–2875, 2009.
27E. Achtert, T. Bernecker, H.-P. Kriegel, E. Schubert, A. Zimek
ELKI in Time: ELKI 0.2 for the Performance Evaluation of Distance Measures for Time Series
In Proceedings of the 11th International Symposium on Spatial and Temporal Databases (SSTD), Aalborg, Denmark: 436–440, 2009.
26H.-P. Kriegel, P. Kröger, E. Schubert, A. Zimek
Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data
In Proceedings of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Bangkok, Thailand: 831–838, 2009.
25H.-P. Kriegel, P. Kröger, E. Schubert, A. Zimek
LoOP: Local Outlier Probabilities
In Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM), Hong Kong, China: 1649–1652, 2009.
24H.-P. Kriegel, P. Kröger, A. Zimek
Outlier Detection Techniques
Tutorial at the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Bangkok, Thailand, 2009.
2008
23H.-P. Kriegel, P. Kröger, A. Zimek
Detecting clusters in moderate-to-high dimensional data: subspace clustering, pattern-based clustering, and correlation clustering
Proceedings of the VLDB Endowment, 1(2): 1528–1529, 2008.
22E. Achtert, C. Böhm, J. David, P. Kröger, A. Zimek
Global Correlation Clustering Based on the Hough Transform
Statistical Analysis and Data Mining, 1(3): 111–127, 2008.
21H.-P. Kriegel, M. Schubert, A. Zimek
Angle-Based Outlier Detection in High-dimensional Data
In Proceedings of the 14th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), Las Vegas, NV: 444–452, 2008.
20H.-P. Kriegel, P. Kröger, E. Schubert, A. Zimek
A General Framework for Increasing the Robustness of PCA-based Correlation Clustering Algorithms
In Proceedings of the 20th International Conference on Scientific and Statistical Database Management (SSDBM), Hong Kong, China: 418–435, 2008.
19E. Achtert, H.-P. Kriegel, A. Zimek
ELKI: A Software System for Evaluation of Subspace Clustering Algorithms
In Proceedings of the 20th International Conference on Scientific and Statistical Database Management (SSDBM), Hong Kong, China: 580–585, 2008.
18J. Aßfalg, J. Gong, H.-P. Kriegel, A. Pryakhin, T. Wei, A. Zimek
Supervised Ensembles of Prediction Methods for Subcellular Localization
In Proceedings of the 6th Annual Asia Pacific Bioinformatics Conference (APBC), Kyoto, Japan: 29–38, 2008.
17E. Achtert, C. Böhm, J. David, P. Kröger, A. Zimek
Robust Clustering in Arbitrarily Oriented Subspaces
In Proceedings of the 8th SIAM International Conference on Data Mining (SDM), Atlanta, GA: 763–774, 2008.
16H.-P. Kriegel, P. Kröger, A. Zimek
Detecting Clusters in Moderate-to-High Dimensional Data: Subspace Clustering, Pattern-based Clustering, and Correlation Clustering
Tutorial at the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Osaka, Japan, 2008.
15H.-P. Kriegel, P. Kröger, A. Zimek
Detecting Clusters in Moderate-to-High Dimensional Data: Subspace Clustering, Pattern-based Clustering, and Correlation Clustering
Tutorial at the 34nd International Conference on Very Large Data Bases (VLDB), Auckland, New Zealand, 2008.
14H.-P. Kriegel, P. Kröger, A. Zimek
Detecting Clusters in Moderate-to-High Dimensional Data: Subspace Clustering, Pattern-based Clustering, and Correlation Clustering
Tutorial at the 14th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), Las Vegas, NV, 2008.
13A. Zimek
Correlation Clustering
PhD Thesis, Ludwig-Maximilians-Universität München, Munich, Germany, 2008.
2007
12H.-P. Kriegel, K. M. Borgwardt, P. Kröger, A. Pryakhin, M. Schubert, A. Zimek
Future Trends in Data Mining
Data Mining and Knowledge Discovery, 15(1): 87–97, 2007.
11S. Brecheisen, H.-P. Kriegel, P. Kröger, M. Pfeifle, M. Schubert, A. Zimek
Density-Based Data Analysis and Similarity Search
In V. A. Petrushin, L. Khan (ed.): Multimedia Data Mining and Knowledge Discovery, Springer: 94–115, 2007.
10E. Achtert, C. Böhm, H.-P. Kriegel, P. Kröger, I. Müller-Gorman, A. Zimek
Detection and Visualization of Subspace Cluster Hierarchies
In Proceedings of the 12th International Conference on Database Systems for Advanced Applications (DASFAA), Bangkok, Thailand: 152–163, 2007.
9E. Achtert, C. Böhm, H.-P. Kriegel, P. Kröger, A. Zimek
On Exploring Complex Relationships of Correlation Clusters
In Proceedings of the 19th International Conference on Scientific and Statistical Database Management (SSDBM), Banff, Canada: 7–16, 2007.
8E. Achtert, C. Böhm, H.-P. Kriegel, P. Kröger, A. Zimek
Robust, Complete, and Efficient Correlation Clustering
In Proceedings of the 7th SIAM International Conference on Data Mining (SDM), Minneapolis, MN: 413–418, 2007.
7H.-P. Kriegel, P. Kröger, A. Zimek
Detecting Clusters in Moderate-to-High Dimensional Data: Subspace Clustering, Pattern-based Clustering, and Correlation Clustering
Tutorial at the 7th International Conference on Data Mining (ICDM), Omaha, NE, 2007.
2006
6E. Achtert, C. Böhm, H.-P. Kriegel, P. Kröger, I. Müller-Gorman, A. Zimek
Finding Hierarchies of Subspace Clusters
In Proceedings of the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), Berlin, Germany: 446–453, 2006.
5E. Achtert, C. Böhm, H.-P. Kriegel, P. Kröger, A. Zimek
Deriving Quantitative Models for Correlation Clusters
In Proceedings of the 12th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), Philadelphia, PA: 4–13, 2006.
4E. Achtert, C. Böhm, P. Kröger, A. Zimek
Mining Hierarchies of Correlation Clusters
In Proceedings of the 18th International Conference on Scientific and Statistical Database Management (SSDBM), Vienna, Austria: 119–128, 2006.
3H.-P. Kriegel, A. Pryakhin, M. Schubert, A. Zimek
COSMIC: Conceptually Specified Multi-Instance Clusters
In Proceedings of the 6th IEEE International Conference on Data Mining (ICDM), Hong Kong, China: 917–921, 2006.
2005
2A. Zimek
Hierarchical Classification Using Ensembles of Nested Dichotomies
Diploma Thesis, Technical University of Munich and Ludwig-Maximilians-Universität München, Munich, Germany, 2005.
2004
1C. Böhm, K. Kailing, P. Kröger, A. Zimek
Computing Clusters of Correlation Connected Objects
In Proceedings of the ACM International Conference on Management of Data (SIGMOD), Paris, France: 455–466, 2004.
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